Bibliographic record
Abstract
According to Foucault discourse can be defined as the articulation of power. Further, political ecologists point out that questions of power, influence, and the environment are anchored in context. Drawing upon these key concepts, originally as a student in Meletis’ third year undergraduate Political Ecology class, and then as I prepared for and later delivered a student presentation at the WDCAG 2017, I aimed to answer the question of who is empowered to lead discourse and define paradigms. In order of doing so, I conducted a literature study reviewto identify influential ideas and actors. I chose to compare works by Arturo Escobar (1996) and Paul Robbins (2012). Based upon their conclusions ‘Western’ influence remains prevalent and powerful, support for the recognition and integration of local environmental knowledge is lacking and Foucault’s theories are key in order to understand underlying power relations. Reflecting upon Foucault’s understandings of power, I also wanted to get ‘us’ - the audience, reflecting on how we understand, explain, interact with, and influence our environment. I wish to highlight the importance of reflecting upon the origins of discourses’ by tracing their evolution and searching for associated agendas, in order to better understand them and their implications. This research note concludes with personal reflections while bearing in mind that ‘we’ are part of the system ourselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".